détails d'emploi
Our client, is seeking a high-performing Specialty Developer V (AI Engineer / MLOps Lead) to join their core technology and digital innovation group.
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In this senior technical role, you will be responsible for designing, building, and deploying cutting-edge AI/ML solutions that enhance enterprise business processes, improve decision-making, and drive advanced automation. Combining software engineering rigor, data science, and machine learning expertise, you will build scalable AI systems in production environments. You will develop end-to-end data pipelines, fine-tune Large Language Model (LLM) applications using modern frameworks (such as LangChain, LangSmith, and OpenAI APIs), and engineer scalable microservices to serve models in real time. Working within a collaborative Agile environment, you will partner closely with data engineering, cloud, and product teams to translate complex business problems into high-impact AI solutions.
Duration: 12-Month Contract (with high potential for extension)
Work Arrangement: Hybrid (4 days per week on-site at the corporate office, 1 day work from home; flexible anchor days)
Advantages
Cutting-Edge Generative AI Scope: Architect, fine-tune, and deploy enterprise-grade LLMs, vector embeddings, and multimodal AI solutions directly into production.
Production MLOps Sandbox: Build end-to-end machine learning pipelines, real-time microservices, and continuous monitoring frameworks for model drift and performance.
12-Month Contract Stability: Secure a full-year contract engagement within a well-funded, top-tier enterprise technology organization.
High Strategic Impact: Bridge the gap between data science research and enterprise delivery, presenting innovative AI capabilities to key internal stakeholders.
Responsibilities
AI/ML Pipeline Engineering & LLM Development
End-to-End Pipeline Development: Design and deploy comprehensive ML pipelines encompassing data preprocessing, feature engineering, model validation, and automated production deployment via CI/CD.
LLM & Generative AI Solutions: Fine-tune and build LLM-based applications using advanced frameworks such as LangChain, LangSmith, and OpenAI APIs.
Microservices & API Architecture: Build scalable, real-time microservices and RESTful APIs to serve ML models within production environments.
Model Governance & Monitoring: Implement continuous monitoring frameworks to detect model drift, track performance metrics, and ensure reliability, data security, and data governance.
Collaboration & Strategic Innovation
Cross-Functional Partnership: Collaborate with data engineering squads to define data requirements and work with structured and unstructured datasets using Python, SQL, Spark, and Pandas.
DevOps & Cloud Integration: Partner with cloud engineers and DevOps teams to ensure secure, containerized, and scalable deployments across cloud environments (AWS, GCP, or Azure).
Research & Prototyping: Evaluate emerging AI tools, frameworks, and model compression techniques; run rapid feasibility prototypes to translate business needs into technical solutions.
Stakeholder Communication: Articulate complex technical concepts and AI capability demonstrations clearly to business partners and non-technical stakeholders.
Qualifications
Python & ML Framework Proficiency: Advanced programming skills in Python, with hands-on mastery of data science and deep learning libraries including NumPy, Pandas, Scikit-learn, PyTorch, or TensorFlow.
Generative AI & NLP Depth: Proven experience developing, fine-tuning, or deploying Large Language Models (LLMs), Natural Language Processing (NLP), or deep learning architectures.
MLOps & Containerization: Strong, practical knowledge of MLOps utilities and container orchestrators such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes.
Cloud Platform & Model Deployment: Direct experience deploying machine learning models to production on major cloud platforms (AWS, GCP, or Azure).
Software Engineering Fundamentals: Solid understanding of data structures, algorithms, object-oriented design, microservices, and software engineering best practices.
Soft Skills: Outstanding verbal and written communication skills; strong analytical and problem-solving mindset; self-motivated, adaptable self-starter with exceptional time management and documentation skills.
Preferred Assets & Nice-to-Haves
Prior experience within a Tier-1 Bank, Financial Institution, or Fintech enterprise.
Direct experience working within an Agile / Scrum delivery environment.
Summary
If you are a tech-savvy AI Engineer and Specialty Developer V who pairs an absolute command of Python, PyTorch/TensorFlow, and LLM frameworks with 12 months of MLOps containerization and cloud model deployment expertise, this hybrid contract is an outstanding opportunity. Bring your pipeline engineering precision, machine learning expertise, and collaborative focus to our client's digital innovation team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
voir plus
Our client, is seeking a high-performing Specialty Developer V (AI Engineer / MLOps Lead) to join their core technology and digital innovation group.
In this senior technical role, you will be responsible for designing, building, and deploying cutting-edge AI/ML solutions that enhance enterprise business processes, improve decision-making, and drive advanced automation. Combining software engineering rigor, data science, and machine learning expertise, you will build scalable AI systems in production environments. You will develop end-to-end data pipelines, fine-tune Large Language Model (LLM) applications using modern frameworks (such as LangChain, LangSmith, and OpenAI APIs), and engineer scalable microservices to serve models in real time. Working within a collaborative Agile environment, you will partner closely with data engineering, cloud, and product teams to translate complex business problems into high-impact AI solutions.
Duration: 12-Month Contract (with high potential for extension)
Work Arrangement: Hybrid (4 days per week on-site at the corporate office, 1 day work from home; flexible anchor days)
Advantages
...
Cutting-Edge Generative AI Scope: Architect, fine-tune, and deploy enterprise-grade LLMs, vector embeddings, and multimodal AI solutions directly into production.
Production MLOps Sandbox: Build end-to-end machine learning pipelines, real-time microservices, and continuous monitoring frameworks for model drift and performance.
12-Month Contract Stability: Secure a full-year contract engagement within a well-funded, top-tier enterprise technology organization.
High Strategic Impact: Bridge the gap between data science research and enterprise delivery, presenting innovative AI capabilities to key internal stakeholders.
Responsibilities
AI/ML Pipeline Engineering & LLM Development
End-to-End Pipeline Development: Design and deploy comprehensive ML pipelines encompassing data preprocessing, feature engineering, model validation, and automated production deployment via CI/CD.
LLM & Generative AI Solutions: Fine-tune and build LLM-based applications using advanced frameworks such as LangChain, LangSmith, and OpenAI APIs.
Microservices & API Architecture: Build scalable, real-time microservices and RESTful APIs to serve ML models within production environments.
Model Governance & Monitoring: Implement continuous monitoring frameworks to detect model drift, track performance metrics, and ensure reliability, data security, and data governance.
Collaboration & Strategic Innovation
Cross-Functional Partnership: Collaborate with data engineering squads to define data requirements and work with structured and unstructured datasets using Python, SQL, Spark, and Pandas.
DevOps & Cloud Integration: Partner with cloud engineers and DevOps teams to ensure secure, containerized, and scalable deployments across cloud environments (AWS, GCP, or Azure).
Research & Prototyping: Evaluate emerging AI tools, frameworks, and model compression techniques; run rapid feasibility prototypes to translate business needs into technical solutions.
Stakeholder Communication: Articulate complex technical concepts and AI capability demonstrations clearly to business partners and non-technical stakeholders.
Qualifications
Python & ML Framework Proficiency: Advanced programming skills in Python, with hands-on mastery of data science and deep learning libraries including NumPy, Pandas, Scikit-learn, PyTorch, or TensorFlow.
Generative AI & NLP Depth: Proven experience developing, fine-tuning, or deploying Large Language Models (LLMs), Natural Language Processing (NLP), or deep learning architectures.
MLOps & Containerization: Strong, practical knowledge of MLOps utilities and container orchestrators such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes.
Cloud Platform & Model Deployment: Direct experience deploying machine learning models to production on major cloud platforms (AWS, GCP, or Azure).
Software Engineering Fundamentals: Solid understanding of data structures, algorithms, object-oriented design, microservices, and software engineering best practices.
Soft Skills: Outstanding verbal and written communication skills; strong analytical and problem-solving mindset; self-motivated, adaptable self-starter with exceptional time management and documentation skills.
Preferred Assets & Nice-to-Haves
Prior experience within a Tier-1 Bank, Financial Institution, or Fintech enterprise.
Direct experience working within an Agile / Scrum delivery environment.
Summary
If you are a tech-savvy AI Engineer and Specialty Developer V who pairs an absolute command of Python, PyTorch/TensorFlow, and LLM frameworks with 12 months of MLOps containerization and cloud model deployment expertise, this hybrid contract is an outstanding opportunity. Bring your pipeline engineering precision, machine learning expertise, and collaborative focus to our client's digital innovation team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
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